Change in anatomical structure of retinal blood vessels (vasculature) in retina is a good indication of the presence of ophthalmic diseases, e.g., hypertension, cardiovascular diseases, diabetic retinopathy, glaucoma, etc. [1]}, [2]}. Vascular map segmentation of fundus images has played a decisive role in assessing the change in the vasculature for severity of ocular diseases. However, periodic screening of retinal images for early recognition of the change in vascular structure can prevent major vision loss [2]}. Therefore, an automatic and accurate retinal vessel segmentation is the prerequisite for the initial diagnosis of retinal diseases. Extraction of the vascular map from an uneven illuminated and pigmented fundus image is a challenging problem. Besides retinal blood vessels, the presence of other structures (e.g., exudates, optic disc, fovea, red lesions) under uneven illuminated and pigmented background makes the vessel detection even more difficult. Also, the retinal vessel thickness varies in the wide range whereas thin vessels have low contrast which makes thin vessel detection more challenging [2]}.
